- author = "Janet Taylor and Jem J. Rowland and Douglas B. Kell",
- title = "Spectral Analysis via Supervised Genetic Search with Application-specific Mutations",
- booktitle = "Proceedings of the 2001 Congress on Evolutionary Computation CEC2001",
- year = "2001",
- pages = "481--486",
- address = "COEX, World Trade Center, 159 Samseong-dong, Gangnam-gu, Seoul, Korea",
- publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
- month = "27-30 " # may,
- organisation = "IEEE Neural Network Council (NNC), Evolutionary Programming Society (EPS), Institution of Electrical Engineers (IEE)",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, biotechnology, supervised, spectroscopy, calibration, IR analytical spectra interpretation, adaptive averaging, application-specific mutations, chemical constituent concentration, complex biological sample, explanatory, expression optimisation, optical spectra, output expression, quasi-continuous properties, selective optimisation, signal-to-noise ratio, spectral analysis, spectral regions, spectral resolution, supervised genetic search, biology computing, infrared spectra, learning (artificial intelligence), spectrochemical analysis, spectroscopy computing",
- ISBN = "0-7803-6658-1",
-
DOI = "
doi:10.1109/CEC.2001.934430",
- abstract = "We present a method in which a genetic algorithm is used to optimise an expression in order to provide a supervised method for interpretation of the infrared analytical spectra of complex biological samples. The aim is to produce a model that can predict the value of a measurand of interest, such as the concentration of a particular chemical constituent, from a complex infrared spectrum of biological material. The method we describe is in some ways analogous to genetic programming but it more readily allows the output expression to be constrained in complexity and permits its general form to be specified by the user, thereby enhancing its explanatory ability. The quasi-continuous properties of optical spectra are exploited by mutations that explore spectral regions adjacent to selected variables, and provide adaptive averaging of spectral regions so as to provide selective optimisation of the tradeoff between spectral resolution and signal-to-noise ratio",
-
notes = "CEC-2001 - A joint meeting of the IEEE, Evolutionary
Programming Society, Galesia, and the IEE.
IEEE Catalog Number = 01TH8546C,
Library of Congress Number =
Hybrid GA-GP? High throughput screening. Fourier transform. E. Coli. Hill climbing. Exponent not useful? Discusses comparison with authors' previous GP approach.",
